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Dataset Title:  Sizes of organisms fixed to flume floor from back reef community flume
experiments conducted in Moorea, French Polynesia, from Nov 2015 to Nov 2016
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_793674)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Flume {
    Byte _FillValue 127;
    Byte actual_range 1, 4;
    String bcodmo_name "tank";
    String description "Flume number (1 = 1400 µatm. 2 = 700 µatm, 3 = 400 µatm, 4 = 1000 µatm)";
    String long_name "Flume";
    String units "unitless";
  ID_number {
    Int16 _FillValue 32767;
    Int16 actual_range 101, 477;
    String bcodmo_name "sample";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Unique organism ID number";
    String long_name "ID Number";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  Species {
    String bcodmo_name "taxon";
    String description "Organism identification (Scientific name or Genus)";
    String long_name "Species";
    String units "unitless";
  Initial {
    Float32 _FillValue NaN;
    Float32 actual_range 57.8, 1115.8;
    String bcodmo_name "mass";
    String description "Initial mass of corals as dry weight calculated from bouyant weight in month 0 (Nov 2015)";
    String long_name "Initial";
    String units "grams (g)";
  Final {
    Float32 _FillValue NaN;
    Float32 actual_range 58.8, 1161.7;
    String bcodmo_name "mass";
    String description "Final mass of corals and algae as dry weight calculated from bouyant weight in month 12 (Nov 2016)";
    String long_name "Final";
    String units "grams (g)";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"The following methodology applies to this dataset in addition to other
datasets published in Edmunds et al. (2019).
Back reef communities were assembled in four flumes, with each randomly
assigned to pCO2 treatments targeting ambient (400 \\u03bcatm), 700 \\u03bcatm,
1000 \\u03bcatm, and 1300 \\u03bcatm pCO2 to approximate atmospheric pCO2
projected for ~ 2140 under representative concentration pathways (RCP) 2.6,
4.5, 6.0 and 8.5, respectively. Treatments were maintained for one year from
November 2015, and actual pCO2 treatments differed from target values. Each
flume consisted of a working section that was 5.0 m long, 30 cm wide and
filled to ~ 30-cm depth with ~ 500 L of seawater that was circulated and
refreshed with sand-filtered (pore size ~ 450\\u2013550 \\u00b5m) seawater from
Cook\\u2019s Bay (-17.491, -149.826, 14-m depth) at ~ 5 L min-1.
Planar growth and community structure were measured because they are used in
ecological analyses of coral reefs, and we reasoned they would sharpen the
ability to interpret the ecological implications of the physiological impacts
of OA on calcification. We anticipated that the community response to OA would
include reduced linear extension, impaired planar growth of tissue and
skeleton, and increase partial mortality (as in Dove et al. 2013). The mean
linear extension expected for the corals in the present study (Porites rus =
15.2 \\u00b1 5.7 mm y-1, massive Porites = 10.0 \\u00b1 0.6 mm y-1, Montipora =
27.7 + 3.0 mm y-1, and Pocillopora verrucosa = 24.7 \\u00b1 2.4 mm y-1
[[https://coraltraits.org/](\\\\\"https://coraltraits.org/\\\\\"), accessed 8
October 2018]) were expected to create annual changes in planar area of 52 cm2
(with mean initial size of 69 cm2), 32 cm2 (with mean initial size of 68 cm2),
106 cm2 (with mean initial size of 70 cm2), and 150 cm2 (with mean initial
size of 218 cm2), respectively, in the ambient flume. To evaluate the
precision of the photographic method, 10 independent images of mounding and
branching corals in the flumes were recorded, and were processed to provide
replicate determinations of organism size (i.e., planar area). These images
showed that the standard deviations of mean area determinations were 2.3% for
massive Porites, and 3.8% for Pocillopora verrucosa). Based on these measures
of precision, there would be a 75% chance of detecting annual growth of 0.6
cm2 for massive Porites and 4.8 cm2 for Pocillopora verrucosa, which represent
reasonable estimates for the growth of these corals in our flumes. Given
effect sizes ranging from 21.1% for Lithophyllum to 10.2% for massive Porites
upon exposure to 1067 \\u00b5atm pCO2 (Comeau et al. 2014), an effect of pCO2
on growth in the present study would be detectable for Montipora, while
smaller effects of pCO2 for other taxa might be prone to Type II errors in
detection (i.e., they might not be detected when present).
Back reef communities were assembled to correspond to the mean percent cover
of the major space holders in this habitat in 2013 (data archived in Edmunds
2015). The Back reef community source was latitude: -17.481, and longitude:
-149.836 \\u00b1 4 km from this point along the north shore. The communities
began with ~ 25% coral cover, with 11% massive Porites spp., 7% Porites rus,
4% Montipora spp., 3% Pocillopora spp., and ~ 7% crustose coralline algae
(CCA), consisting of 4% Porolithon onkodes and 3% Lithophyllum kotschyanum.
Coral rubble (~ 1-cm diameter) was added to ~ 5% cover, and the remainder of
the benthic surface was sand. Analyses of community structure focused on the
central, 2.4-m long portion of this community where corals and CCA were
secured to a plastic-coated, metal grid (5 \\u00d7 5 cm mesh) and represented
the \\u201cfixed\\u201d community. Securing organisms to the grid was critical
to reduce parallax errors in photography, to allow the organisms to grow and
interact as they extended over the year experiment, and to allow ecologically
meaningful analysis of community structure using photographs.
The central section of each flume included a 2.4-m long sediment box that
extended the width of the flume, and contained 30-cm depth of sediment. The
sediment box was flanked by ~ 2.6 m of the fiberglass floor of the flume,
along which 0.8 m was occupied by the same benthic community, but with corals
and CCA resting on the bottom (i.e., \\u201cunfixed\\u201d). Members of the
fixed community were buoyant weighed at the start and end of the year to
measure Net changes in mass (Gnet), but otherwise were left in place. Members
of the unfixed community were removed monthly to measure buoyant weight to
calculate Gnet (described below). The unfixed portion of the community allowed
monthly resolution of Gnet, but the necessity for removal from (and return to)
the flume to measure Gnet resulted in relocation error that negated their use
in photographic measurement of community structure. In addition to the coral,
sand, CCA, and rubble, the flumes were augmented with holothurians (~ 8-cm
long, Holothuria spp.), and macroalgae (Turbinaria ornata and Halimeda minima)
to approximate the cover of these algae in the back reef in 2013 (~
Corals, CCA, and rubble were collected from ~ 2-m depth in the back reef, and
were attached with epoxy (Z-Spar A788) to plastic bases. Sediments were
collected in the same location, and were placed into boxes that were buried in
situ, flush with the sediment for 3 d to promote stratification, and then
installed in each flume. Back reef communities were constructed in the flumes
on 12 November 2015, and were maintained under ambient conditions until 17
November 2015, when pCO2 treatments began in three flumes, with levels
increased to target values over 24 h. Throughout the experiment, the flumes
were cleaned of algal turf that grew on the walls of the flumes as well as
exposed plastic and the metal grid on the floor of the flume. Turfs were not
removed from natural surfaces (i.e., coral bases and rubble) with the
rationale that they are a normal component of back reef communities.
Physical and chemical parameters:
Seawater was circulated at ~ 0.1 m s-1 using a pump (W. Lim Wave II 373 J
s-1), and flow speeds were measured across the working sections using a Nortek
Vectrino Acoustic Doppler Velocimeter. This flow speed was relevant for the
back reef of Mo'orea. The flumes were exposed to sunlight that was shaded to a
photon flux density (PFD) of photosynthetically active radiation (PAR)
approximating 2-m depth in the back reef. Light was measured using cosine-
corrected sensors (Odyssey, Dataflow Systems Ltd, New Zealand) that were
calibrated with a LI-COR meter (LI-1400, Li-COR Biosciences, Lincoln, NE)
attached to a 2\\u03c0 sensor (LI 192A). Maximum daily PFD varied by day and
season from 364\\u20131,831 \\u03bcmol quanta m-2 s-1. Temperatures were
regulated close to the mean monthly temperature in the back reef that
increased from ~ 27.8\\u00b0C in December 2015, to ~29.3\\u00b0C in April 2016,
and back to ~ 27.4 \\u00b0C in November 2016.
Seawater carbonate chemistry was uncontrolled in one flume (ambient), and in
the three others, seawater pH was controlled through the addition of CO2 gas
(using solenoids controlled with an Aquacontroller, Neptune Systems, USA) to
approximate pCO2 targets. A diurnal upward adjustment of ~ 0.1 pH was applied
to the treatments to simulate natural variation in seawater pCO2 in the back
reef. The ambient flume also maintained a diurnal variation in pCO2 with a
nighttime pH ~ 0.1 lower than daytime. Ambient air was bubbled into all
PAR and temperature (Hobo Pro v2 [\\u00b1 0.2\\u00b0C], Onset Computer Corp.,
MA, USA) were recorded, and pH was measured daily (at various times of day) on
the total hydrogen ion scale (pHT). Temperature and pH were used to adjust the
thermostat and pH-set points close to values that were calculated (using
seacarb) to correspond to target treatments of 400 \\u00b5atm, 700 \\u00b5atm,
1000 \\u00b5atm, and 1300 \\u00b5atm (~ 8.04, ~7.81, ~7.70 and ~7.65,
respectively). Seawater carbonate chemistry (pH and AT) and salinity were
measured at 14:00 hrs and 20:00 hrs weekly. A conductivity meter (Thermo
Scientific, Orionstar A212, Waltham, MA, USA) was used to measure salinity.
The remaining parameters of the seawater carbonate system were calculated from
temperature, salinity, pHT, and AT, using the R package seacarb. Calculations
were made using the carbonic acid dissociation constants, the KSO4
concentration for the bisulfate ion, and the Kf constant.
pHT was measured using a DG 115-SC electrode (Mettler Toledo, Columbus, OH,
USA) that was calibrated with a TRIS buffers. AT was measured using open-cell,
acidimetric titration (SOP 3b [Dickson et al. 2007]) using certified titrant
with a titrator (T50 with a DG 115-SC electrode, Mettler Toledo). The accuracy
and precision of measurements were determined using reference materials (from
A. Dickson, Scripps Institution of Oceanography, CA, USA), against which
measured values of AT maintained an accuracy of 1.7 \\u00b1 0.3 \\u03bcmol kg-1
(n = 15) and precision of 1.8 \\u00b1 0.1 \\u03bcmol kg-1 (n = 475).
Response variables:
Net changes in mass (Gnet) of corals and CCA was measured using buoyant weight
(\\u00b1 1 mg) by month (unfixed) or year (fixed community). Buoyant weight was
converted to dry weight of CaCO3 using empirical seawater density (~1.02278 g
cm-3) and the density of pure aragonite (2.93 g cm-3, corals) and pure calcite
(2.71 g cm-3, CCA). Gnet in each month was expressed as the percentage change
in mass relative to the initial mass in November 2015. As the area of tissue
changed throughout the experiment through growth and partial mortality,
\\u201cgrowth\\u201d could not be expressed on an area-normalized scale.
Community structure was quantified using planar photographs recorded in
ambient light using a GoPro Hero 4 camera (12 MP, 3-mm focal length). The
camera was moved along the flume to record the community in the working
section using ~ 16 frames sampling-1.
Photographs were analyzed using ImageJ software, in which the planar area of
living tissue on corals and CCA was quantified by outlining organisms and
scaling the image using the metal grid as a reference. Size (cm2) was
expressed as a percentage of the area (240 \\u00d7 30 = 7200 cm2) occupied by
the fixed members of the community. The summed area of community members was
used to determine overall cover of the benthic community, and changes in area
were used to quantify growth. Where organisms died, their area was set to
See Edmunds et al. (2019) for analyses that used these data.";
    String awards_0_award_nid "536317";
    String awards_0_award_number "OCE-1415268";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1415268";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "David L. Garrison";
    String awards_0_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"Edmunds et al. 2019b: Sizes of organisms fixed to flume floor 
  PI: Peter J. Edmunds 
  Data Version 1: 2020-02-18";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String dataset_current_state "Final and no updates";
    String date_created "2020-02-18T20:17:27Z";
    String date_modified "2020-02-26T16:23:14Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.793674.1";
    String history 
"2022-08-09T11:31:37Z (local files)
2022-08-09T11:31:37Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_793674.das";
    String infoUrl "https://www.bco-dmo.org/dataset/793674";
    String institution "BCO-DMO";
    String instruments_0_acronym "camera";
    String instruments_0_dataset_instrument_nid "793681";
    String instruments_0_description "All types of photographic equipment including stills, video, film and digital systems.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/311/";
    String instruments_0_instrument_name "Camera";
    String instruments_0_instrument_nid "520";
    String keywords "bco, bco-dmo, biological, chemical, data, dataset, dmo, erddap, final, flume, ID_number, initial, management, number, oceanography, office, preliminary, species";
    String license "https://www.bco-dmo.org/dataset/793674/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/793674";
    String param_mapping "{'793674': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/793674/parameters";
    String people_0_affiliation "California State University Northridge";
    String people_0_affiliation_acronym "CSU-Northridge";
    String people_0_person_name "Peter J. Edmunds";
    String people_0_person_nid "51536";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "California State University Northridge";
    String people_1_affiliation_acronym "CSU-Northridge";
    String people_1_person_name "Steve Doo";
    String people_1_person_nid "748154";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "California State University Northridge";
    String people_2_affiliation_acronym "CSU-Northridge";
    String people_2_person_name "Robert Carpenter";
    String people_2_person_nid "51535";
    String people_2_role "Contact";
    String people_2_role_type "related";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Amber D. York";
    String people_3_person_nid "643627";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "OA coral adaptation";
    String projects_0_acronym "OA coral adaptation";
    String projects_0_description 
"Extracted from the NSF award abstract:
This project focuses on the most serious threat to marine ecosystems, Ocean Acidification (OA), and addresses the problem in the most diverse and beautiful ecosystem on the planet, coral reefs. The research utilizes Moorea, French Polynesia as a model system, and builds from the NSF investment in the Moorea Coral Reef Long Term Ecological Research Site (LTER) to exploit physical and biological monitoring of coral reefs as a context for a program of studies focused on the ways in which OA will affect corals, calcified algae, and coral reef ecosystems. The project builds on a four-year NSF award with research in five new directions: (1) experiments of year-long duration, (2) studies of coral reefs to 20-m depth, (3) experiments in which carbon dioxide will be administered to plots of coral reef underwater, (4) measurements of the capacity of coral reef organisms to change through evolutionary and induced responses to improve their resistance to OA, and (5) application of emerging theories to couple studies of individual organisms to studies of whole coral reefs. Broader impacts will accrue through a better understanding of the ways in which OA will affect coral reefs that are the poster child for demonstrating climate change effects in the marine environment, and which provide income, food, and coastal protection to millions of people living in coastal areas, including in the United States. 
This project focuses on the effects of Ocean Acidification on tropical coral reefs and builds on a program of research results from an existing 4-year award, and closely interfaces with the technical, hardware, and information infrastructure provided through the Moorea Coral Reef (MCR) LTER. The MCR-LTER, provides an unparalleled opportunity to partner with a study of OA effects on a coral reef with a location that arguably is better instrumented and studied in more ecological detail than any other coral reef in the world. Therefore, the results can be both contextualized by a high degree of ecological and physical relevance, and readily integrated into emerging theory seeking to predict the structure and function of coral reefs in warmer and more acidic future oceans. The existing award has involved a program of study in Moorea that has focused mostly on short-term organismic and ecological responses of corals and calcified algae, experiments conducted in mesocosms and flumes, and measurements of reef-scale calcification. This new award involves three new technical advances: for the first time, experiments will be conducted of year-long duration in replicate outdoor flumes; CO2 treatments will be administered to fully intact reef ecosystems in situ using replicated underwater flumes; and replicated common garden cultivation techniques will be used to explore within-species genetic variation in the response to OA conditions. Together, these tools will be used to support research on corals and calcified algae in three thematic areas: (1) tests for long-term (1 year) effects of OA on growth, performance, and fitness, (2) tests for depth-dependent effects of OA on reef communities at 20-m depth where light regimes are attenuated compared to shallow water, and (3) tests for beneficial responses to OA through intrinsic, within-species genetic variability and phenotypic plasticity. Some of the key experiments in these thematic areas will be designed to exploit integral projection models (IPMs) to couple organism with community responses, and to support the use of the metabolic theory of ecology (MTE) to address scale-dependence of OA effects on coral reef organisms and the function of the communities they build.
The following publications and data resulted from this project:
Comeau S, Carpenter RC, Lantz CA, Edmunds PJ. (2016) Parameterization of the response of calcification to temperature and pCO2 in the coral Acropora pulchra and the alga Lithophyllum kotschyanum. Coral Reefs 2016. DOI 10.1007/s00338-016-1425-0.calcification rates (2014)calcification rates (2010)
Comeau, S., Carpenter, R.C., Edmunds, P.J.  (2016) Effects of pCO2 on photosynthesis and respiration of tropical scleractinian corals and calcified algae. ICES Journal of Marine Science doi:10.1093/icesjms/fsv267.respiration and photosynthesis Irespiration and photosynthesis II
Evensen, N.R. & Edmunds P. J. (2016) Interactive effects of ocean acidification and neighboring corals on the growth of Pocillopora verrucosa. Marine Biology, 163:148. doi: 10.1007/s00227-016-2921-zcoral growthseawater chemistrycoral colony interactions";
    String projects_0_end_date "2018-12";
    String projects_0_geolocation "Moorea, French Polynesia";
    String projects_0_name "Collaborative Research: Ocean Acidification and Coral Reefs: Scale Dependence and Adaptive Capacity";
    String projects_0_project_nid "535322";
    String projects_0_project_website "http://mcr.lternet.edu";
    String projects_0_start_date "2015-01";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "These data describe the fauna that was secured to a metal grid in the bottom of the flume.  These data are results of an experiment incubating a back reef community from Moorea, French Polynesia, for one year at high pCO2 (published in Edmunds et al. 2019) from Nov of 2015 to Nov of 2016.";
    String title "Sizes of organisms fixed to flume floor from back reef community flume experiments conducted in Moorea, French Polynesia, from Nov 2015 to Nov 2016";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.5";


Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
For example,
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.

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